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Research on intelligent scheduling algorithm of high altitude platform system for wide area internet of things

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Abstract

Internet of things technology can not only improve people’s lives, but also bring great changes and innovations to the industry and promote the rapid development of economy. The future communication system will be a system of everything connected with IoT. There will be various types of user equipment in the system. The standards adopted by different types of equipment are different, and the required business levels are also different. This will bring great challenges to the resource allocation of the system. Artificial intelligence algorithms provide technical support for future intelligent wireless systems. The system can select appropriate artificial intelligence algorithms according to different application scenarios and establish more accurate mathematical models to serve the network. According to the business priority analysis of user equipment under the wide area Internet of things, considering the user scheduling as the constraint condition, a high-altitude platform user equipment scheduling model based on artificial intelligence k-means algorithm under the user scheduling constraint condition is established. Based on the user equipment scheduling model of high-altitude platform based on artificial intelligence k-means algorithm, a two-stage K-means improved algorithm is proposed to cluster the user equipment of wide area Internet of things, which is divided into preprocessing training stage and K-means algorithm clustering stage. The initial center value is not randomly selected. In the preprocessing training stage, the scheduling priority of each user is obtained according to the channel environment and packet length of the user equipment. The first k user equipment with the same scheduling priority is used as the initial clustering points to complete the preprocessing training. Then, K-means algorithm is used to cluster the new user equipment to be scheduled until convergence. The intelligent scheduling of user equipment under the wide area Internet of things is realized.

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Acknowledgements

This paper is supported by the Guangdong Province higher vocational colleges & schools Pearl River scholar funded scheme (2016),Research platform and project of Department of Education of Guangdong Province (2019GGCZX009), the Key laboratory of Longgang District (LGKCZSYS2018000028), the Scientific and Technological Projects of Shenzhen (No. JCYJ20190808093001772), Research on key technologies of short text automatic scoring based on deep learning and its application in intelligent education (This work is supported by Department of Education of Guangdong Province (Number: 2020KTSCX301)), Stable Support Plan for Colleges and Universities of Shenzhen (SZIITWDZC2021B03), Project of Educational Commission of Guangdong Province of China (2019GKQNCX122) and the scientific research project in school-level (SZIIT2019KJ026).

Funding

Guangdong Province higher vocational colleges and schools, the Pearl River scholar funding scheme,2016, Mingxiang Guan, research platform and project of the Department of Education of Guangdong Province, 2019GGCZX009, Mingxiang Guan, key laboratory of Long gang District, LGKCZSYS2018000028,Scientific and Technological Projects of Shenzhen, JCYJ20190808093001772, Research on key technologies of short text automatic scoring based on deep learning and its application in intelligent education, 2020KTSCX301, Zhou Wu, Stable Support Plan for Colleges and Universities of Shenzhen, SZIITWDZC2021B03, Zhou Wu, Project of Educational Commission of Guangdong Province of China, 2019GKQNCX122, Zhou Wu, the scientific research project in school-level, SZIIT2019KJ026, Zhou Wu

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Authors and Affiliations

  1. Shenzhen Institute of Information Technology, Shenzhen, 518172, China

    Zhou Wu, Mingxiang Guan, Ming Liu, Linzhong Xia, Changwei Lv, Xuemei Cao & Hanying Chen

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  1. Zhou Wu
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  2. Mingxiang Guan
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  3. Ming Liu
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Correspondence to Ming Liu.

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Wu, Z., Guan, M., Liu, M. et al. Research on intelligent scheduling algorithm of high altitude platform system for wide area internet of things. Wireless Netw 30, 4017–4023 (2024). https://doi.org/10.1007/s11276-021-02842-5

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